Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Sybilproof reputation mechanisms
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Lottery trees: motivational deployment of networked systems
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Mechanisms for multi-level marketing
Proceedings of the 12th ACM conference on Electronic commerce
Proceedings of the 13th ACM Conference on Electronic Commerce
Simpler sybil-proof mechanisms for multi-level marketing
Proceedings of the 13th ACM Conference on Electronic Commerce
No need to war-drive: unsupervised indoor localization
Proceedings of the 10th international conference on Mobile systems, applications, and services
Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing
Proceedings of the 18th annual international conference on Mobile computing and networking
Zee: zero-effort crowdsourcing for indoor localization
Proceedings of the 18th annual international conference on Mobile computing and networking
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We study Incentive Tree for motivating the participation of people in crowdsourcing or human tasking systems. In an Incentive Tree, each participant is rewarded for contributing to the system, as well as for soliciting new participants into the system, who then themselves contribute to it and/or themselves solicit new participants. An Incentive Tree mechanism is an algorithm that determines how much reward each individual participant receives based on all the participants' contributions, as well as the structure of the solicitation tree. The sum of rewards paid by the mechanism to all participants is linear in the sum of their total contribution. In this paper, we investigate the possibilities and limitations of Incentive Trees via an axiomatic approach by defining a set of desirable properties that an incentive tree mechanism should satisfy. We give a mutual incompatibility result showing that there is no incentive tree mechanism that simultaneously achieves all the properties. We then present two novel families of incentive tree mechanisms. The first family of mechanisms achieves all desirable properties, except that it fails to protect against a certain strong form of multi-identity attack; the second set of mechanisms achieves all properties, including the strong multi-identity protection, but fails to give participants the opportunity to achieve unbounded reward. Given the above impossibility result, these two mechanisms are effectively the best we can hope for. Finally, our model and results generalize recent studies on multi-level marketing mechanisms.